Active Cancer Brain & Nervous System

Mac4Me Macrophage Targets for Metastatic Treatment

In plain English

AI plain-English summary

Around 300,000 people in the EU with metastatic neuroblastoma, breast, or prostate cancer do not respond to current immunotherapies, and this project aims to find out why by studying how tumour cells interact with the immune system at the site of metastasis. Existing immunotherapies work well for only a few cancer types. The problem is that researchers do not fully understand the molecular and mechanical changes that tumour cells trigger in the immune system and surrounding tissue when they spread to new organs. This project fills that gap by focusing on the specific interactions between tumour cells and host immune cells in the brain, bone, and liver—the most common sites for metastasis in these cancers. If successful, the research could identify new immune targets for therapies that work against currently untreatable metastatic cancers. The project uses animal-free organ-on-chip systems to model early metastasis, then validates findings against real clinical data using AI machine learning. This approach could accelerate the development of more effective immunotherapies for patients who currently have no good options. The project also trains a new generation of scientists in participatory science, bringing patient and public expectations into the research process from the start. This could shift how future cancer treatments are designed and evaluated, making shared decision-making a standard part of health care solutions for incurable disease.

View original technical description
Immunotherapies promise to be the major break-through in the treatment of metastatic cancer, but effectiveness is limited to few cancer types. Metastatic neuroblastoma, breast and prostate cancer, affecting approximately 300,000 EU-27 inhabitants of all age groups in 2020, respond not or very poorly to current immunotherapies. To establish more effective immunotherapies, we need to better understand the specific tumour cell-immune host interactions at the metastatic site. The Mac4Me Doctoral Network adopts an innovative, multidisciplinary and cross-sectional approach, with a unique and dedicated research training programme to equip young researchers with scientific knowledge and transferable skills that are essential for today's great demand in both academic and non-academic sectors. Mac4Me aims to understand the tumour cell-immune host interactions at the metastatic site. with an in-depth molecular and mechanistic understanding of the immune and matrix changes induced by tumour cells. We will use innovative animal-free organ-on-chip systems, that recapitulate early metastasis formation of brain, bone and liver. The retrieved knowledge from the preclinical models will be integrated in data from established clinical metastases and AI machine learning algorithms will be applied to identify new immune targets. Mac4Me will align with patients and the general public from the very beginning thereby bringing societal expectations and patient needs into the centre of the project to pave the way for new standards for shared decision making and acceptable health care solutions. Mac4Me will prepare a next generation of young scientists to start their own career as independent researchers being equipped with scientific knowledge and personal skills and integrating participatory science as a starting point to address the societal demand for more effective treatment solutions for incurable metastatic disease, such as neuroblastoma, breast and prostate cancer.

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Researchers

Cathy Merry (Co-Investigator)Johnathan Curd (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

Macrophage Targets for Metastatic Treatment
Characterising neutrophil:macrophage cross-talk in metastatic niches
Combination Therapy for the Treatment of Metastatic MELanOma Using MAgnetic NanoparticlES
Novel Synthetic Biology Approach to Monitor Transient Tumour-Immune Cell Interaction in vivo
Novel therapeutic approaches to target cancer spread in the brain

Original classification

Training Grant

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